University of California, Irvine

About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.

LSST: From Science Drivers to Reference Design and Anticipated Data Products

Abstract: We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachon in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320–1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r ~ 27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

Emended description of the order Chlamydiales, proposal of Parachlamydiaceae fam. nov. and Simkaniaceae fam. nov., each containing one monotypic genus, revised taxonomy of the family Chlamydiaceae, including a new genus and five new species, and standards for the identification of organisms.

Abstract: The current taxonomic classification of Chlamydia is based on limited phenotypic, morphologic and genetic criteria This classification does not take into account recent analysis of the ribosomal operon or recently identified obligately intracellular organisms that have a chlamydia-like developmental cycle of replication Neither does it provide a systematic rationale for identifying new strains In this study, phylogenetic analyses of the 16S and 23S rRNA genes are presented with corroborating genetic and phenotypic information to show that the order Chlamydiales contains at least four distinct groups at the family level and that within the Chlamydiaceae are two distinct lineages which branch into nine separate clusters In this report a reclassification of the order Chlamydiales and its current taxa is proposed This proposal retains currently known strains with > 90% 16S rRNA identity in the family Chlamydiaceae and separates other chlamydia-like organisms that have 80--90% 16S rRNA relatedness to the Chlamydiaceae into new families Chlamydiae that were previously described as ‘Candidatus Parachlamydia acanthamoebae’ Amann, Springer, Schonhuber, Ludwig, Schmid, Muller and Michel 1997, become members of Parachlamydiaceae fam nov, Parachlamydia acanthamoebae gen nov, sp nov ‘Simkania’ strain Z becomes the founding member of Simkaniaceae fam nov, Simkania negevensis gen nov, sp nov The fourth group, which includes strain WSU 86--1044, was left unnamed The Chlamydiaceae, which currently has only the genus Chlamydia, is divided into two genera, Chlamydia and Chlamydophila gen nov Two new species, Chlamydia muridarum sp nov and Chlamydia suis sp nov, join Chlamydia trachomatis in the emended genus Chlamydia Chlamydophila gen nov assimilates the current species, Chlamydia pecorum, Chlamydia pneumoniae and Chlamydia psittaci, to form Chlamydophila pecorum comb nov, Chlamydophila pneumoniae comb nov and Chlamydophila psittaci comb nov Three new Chlamydophila species are derived from Chlamydia psittaci: Chlamydophila abortus gen nov, sp nov, Chlamydophila caviae gen nov, sp nov and Chlamydophila felis gen nov, sp nov Emended descriptions for the order Chlamydiales and for the family Chlamydiaceae are provided These families, genera and species are readily distinguished by analysis of signature sequences in the 165 and 235 ribosomal genes

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Abstract: The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.